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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1996

A Detailed Level Kinetics Model of NO Vibrational Energy Distributions

Several contemporary problems have pointed to the desirability of a detailed level kinetics approach to modeling the distribution of vibrational energy in NO. Such a model is necessary when vibrational redistribution reactions are insufficient to maintain a Boltzmann distribution over the vibrational energy states. Recent calculations of the rate constant for the first reaction of the Zeldovich mechanism (N2 + O (goes to) NO + N) have suggested that the product NO is formed in high vibrational states. In shock layer flowfields, the product NO molecules may experience an insufficient number of collisions to establish a Boltzmann distribution over vibrational states, thus necessitating a level kinetics model. In other flows, such as expansions of high temperature air, fast, near-resonance vibrational energy exchanges with N2 and O2 may also require a level specific model for NO because of the relative rates of vibrational exchange and redistribution. The proposed report will integrate computational and experimental components to construct such a model for the NO molecule.

Sharma, Surendra P.↗

NASA NTRS2013

Software to Compare NPP HDF5 Data Files

This software was developed for the NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project (NPP) Science Data Segment. The purpose of this software is to compare HDF5 (Hierarchical Data Format) files specific to NPP and report whether the HDF5 files are identical. If the HDF5 files are different, users have the option of printing out the list of differences in the HDF5 data files. The user provides paths to two directories containing a list of HDF5 files to compare. The tool would select matching HDF5 file names from the two directories and run the comparison on each file. The user can also select from three levels of detail. Level 0 is the basic level, which simply states whether the files match or not. Level 1 is the intermediate level, which lists the differences between the files. Level 2 lists all the details regarding the comparison, such as which objects were compared, and how and where they are different. The HDF5 tool is written specifically for the NPP project. As such, it ignores certain attributes (such as creation_date, creation_ time, etc.) in the HDF5 files. This is because even though two HDF5 files could represent exactly the same granule, if they are created at different times, the creation date and time would be different. This tool is smart enough to ignore differences that are not relevant to NPP users.

Wiegand, Chiu P.↗

NASA NTRS2012

Large Terrain Continuous Level of Detail 3D Visualization Tool

This software solved the problem of displaying terrains that are usually too large to be displayed on standard workstations in real time. The software can visualize terrain data sets composed of billions of vertices, and can display these data sets at greater than 30 frames per second. The Large Terrain Continuous Level of Detail 3D Visualization Tool allows large terrains, which can be composed of billions of vertices, to be visualized in real time. It utilizes a continuous level of detail technique called clipmapping to support this. It offloads much of the work involved in breaking up the terrain into levels of details onto the GPU (graphics processing unit) for faster processing.

Myint, Steven↗

NASA NTRS2023

Development of Level of Detail System and First-Person Camera for the GCAS Visualization Suite

The use of data-driven simulations has become standard practice as part of planning for future space missions. These simulations allow visualizing the data interactively to show what the data represents, as well as the importance of the data in the context of the mission. Using this visualized data can enhance users’ understanding of it and accelerate analysis efforts related to missions planned around it. Three-dimensional (3D) visualization software was developed to allow creating 3D representations of various communication systems, as well as the physical terrain of the Moon, for upcoming missions. The goal of this software development effort was to create interactive visualization capabilities in the Glenn Research Center Communication Analysis Suite (GCAS) using data exported from MATLAB® (MathWorks, Inc.) scripts. This software had the functionality to visualize the line of sight and dynamic link margins of the communication satellites orbiting the Earth and the Moon. One important addition to this was the visualization of the terrain data located within the GeoTIFF files, which were produced in an effort to understand the Moon’s terrain. Proper displacement values of this data have to be visualized to showcase where craters are located and how the shadow casting works with said craters at different points of the day, as well as analysis of possible landing sites for future lunar expeditions. The graphics library coded in JavaScript, three.js, had been previously selected for developing this visualization software. The software was revised to conform to modern standards, then further developed to convert the MATLAB® data into JavaScript 3D objects and Blender GL Transmission Format Binary file (GLB) objects, which were to be imported into the scene. In the process, a variety of other testing projects were created to be combined with this project at a later point; these included the first-person camera movements around spherical objects to portray human movement around the Moon, GeoTIFF loading methods, data transfer methods for incorporating the elevation data into the scene, and level of detail (LOD) capabilities to decrease memory usage and rendering time.

Visualization↗

NASA NTRS2013

Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data

Web-based geospatial client applications such as Google Earth and NASA World Wind must listen to data requests, access appropriate stored data, and compile a data response to the requesting client application. This process occurs repeatedly to support multiple client requests and application instances. Newer Web-based geospatial clients also provide user-interactive functionality that is dependent on fast and efficient server responses. With massively large datasets, server-client interaction can become severely impeded because the server must determine the best way to assemble data to meet the client applications request. In client applications such as Google Earth, the user interactively wanders through the data using visually guided panning and zooming actions. With these actions, the client application is continually issuing data requests to the server without knowledge of the server s data structure or extraction/assembly paradigm. A method for efficiently controlling the networked access of a Web-based geospatial browser to server-based datasets in particular, massively sized datasets has been developed. The method specifically uses the Keyhole Markup Language (KML), an Open Geospatial Consortium (OGS) standard used by Google Earth and other KML-compliant geospatial client applications. The innovation is based on establishing a dynamic cascading KML strategy that is initiated by a KML launch file provided by a data server host to a Google Earth or similar KMLcompliant geospatial client application user. Upon execution, the launch KML code issues a request for image data covering an initial geographic region. The server responds with the requested data along with subsequent dynamically generated KML code that directs the client application to make follow-on requests for higher level of detail (LOD) imagery to replace the initial imagery as the user navigates into the dataset. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics. The method yields significant improvements in userinteractive geospatial client and data server interaction and associated network bandwidth requirements. The innovation uses a C- or PHP-code-like grammar that provides a high degree of processing flexibility. A set of language lexer and parser elements is provided that offers a complete language grammar for writing and executing language directives. A script is wrapped and passed to the geospatial data server by a client application as a component of a standard KML-compliant statement. The approach provides an efficient means for a geospatial client application to request server preprocessing of data prior to client delivery. Data is structured in a quadtree format. As the user zooms into the dataset, geographic regions are subdivided into four child regions. Conversely, as the user zooms out, four child regions collapse into a single, lower-LOD region. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics.

Baxes, Gregory↗

NASA NTRS1991

Robust fault diagnosis of physical systems in operation

Ideas are presented and demonstrated for improved robustness in diagnostic problem solving of complex physical systems in operation, or operative diagnosis. The first idea is that graceful degradation can be viewed as reasoning at higher levels of abstraction whenever the more detailed levels proved to be incomplete or inadequate. A form of abstraction is defined that applies this view to the problem of diagnosis. In this form of abstraction, named status abstraction, two levels are defined. The lower level of abstraction corresponds to the level of detail at which most current knowledge-based diagnosis systems reason. At the higher level, a graph representation is presented that describes the real-world physical system. An incremental, constructive approach to manipulating this graph representation is demonstrated that supports certain characteristics of operative diagnosis. The suitability of this constructive approach is shown for diagnosing fault propagation behavior over time, and for sometimes diagnosing systems with feedback. A way is shown to represent different semantics in the same type of graph representation to characterize different types of fault propagation behavior. An approach is demonstrated that threats these different behaviors as different fault classes, and the approach moves to other classes when previous classes fail to generate suitable hypotheses. These ideas are implemented in a computer program named Draphys (Diagnostic Reasoning About Physical Systems) and demonstrated for the domain of inflight aircraft subsystems, specifically a propulsion system (containing two turbofan systems and a fuel system) and hydraulic subsystem.

Abbott, Kathy Hamilton↗

NASA NTRS2005

Destructive physical analysis of hollow cathodes from the Deep Space 1 Flight spare ion engine 30,000 hr life test

Destructive physical analysis of the discharge and neutralizer hollow cathode assemblies from the Deep Space 1 Flight Spare 30,000 Hr life test was performed to characterize physical and chemical evidence of operationally induced effects after 30,372 hours of operation with beam extraction. Post-test inspection of the discharge-cathode assembly was subdivided into detailed analyses at the subcomponent level. Detailed materials analysis and optical inspection of the insert, orifice plate, cathode tube, heater, keeper assembly, insulator, and low-voltage propellant isolator were performed. Energy dispersive X-ray (EDX) and scanning electron microscopy (SEW analyses were used to determine the extent and composition of regions of net deposition and erosion of both the discharge and neutralizer inserts. A comparative approach with an un-operated 4:1:1 insert was used to determine the extent of impregnate material depletion as a function of depth from the ID surface and axial position from the orifice plate. Analysis results are compared and contrasted with those obtained from similar analyses on components from shorter term tests, and provide insight regarding the prospect for successful longer-term operation consistent with SOA ion engine program life objectives at NASA.

cathodes↗

NASA NTRS1994

A Cost and Performance System (CAPS) in a Federal agency

Cost and Performance System (CAPS) is an automated system used from the planning phase through implementation to analysis and documentation. Data is retrievable or available for analysis of cost versus performance anomalies. CAPS provides a uniform system across intra- and international elements. A common system is recommended throughout an entire cost or profit center. Data can be easily accumulated and aggregated into higher levels of tracking and reporting of cost and performance.The level and quality of performance or productivity is indicated in the CAPS model and its process. The CAPS model provides the necessary decision information and insight to the principal investigator/project engineer for a successful project management experience. CAPS provides all levels of management with the appropriate detailed level of data.

Huseonia, W. F.↗

NASA NTRS2020

A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems’ Worldviews

Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot’s abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi- robot system autonomously schedules which robots should perform a given task and when, using its worldview–the robot’s internal representation of its belief about the environment and other robots’ states. A key problem for operators is that robots’ worldviews can fall out of sync (often due to weak communication links), leading to desynchronization of the robots’ scheduling decisions and inconsistent emergent behavior (e.g., tasks not performed, or performed by multiple robots). Operators face the time-consuming and difficult task of making sense of the robots’ scheduling decisions, detecting de-synchronizations, and pinpointing their cause by comparing every robot’s worldview. To address these challenges, we introduce MOSAIC Viewer, a visual analytics system that helps operators (i) make sense of the robots’ schedules and (ii) detect and conduct a root cause analysis of the robots’ desynchronized worldviews. Over a year-long partnership with roboticists at the NASA Jet Propulsion Laboratory, a formative study was performed to identify the necessary system design requirements, which supports the design of the system. A qualitative study with 12 roboticists reveals that MOSAIC Viewer is faster- and easier-to-use than the users’ current approaches, and it allows them to stitch low-level details to formulate a high-level understanding of the robots’ schedules and detect and pin-point the cause of desynchronized worldviews.

Ma, Kwan-Liu↗

NASA NTRS2013

Multi-Dimensional Damage Detection for Surfaces and Structures

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or sensory system, which may include a time domain reflectometer, resistivity monitoring hardware, or other resistance-based systems. To begin, a layered composite consisting of thin-film damage detection layers separated by non-damage detection layers is fabricated. The damage detection layers are attached to a detector that provides details regarding the physical health of each detection layer individually. If damage occurs to any of the detection layers, a change in the electrical properties of the detection layers damaged occurs, and a response is generated. Real-time analysis of these responses will provide details regarding the depth, location, and size estimation of the damage. Multiple damages can be detected, and the extent (depth) of the damage can be used to generate prognostic information related to the expected lifetime of the layered composite system. The detection system can be fabricated very easily using off-the-shelf equipment, and the detection algorithms can be written and updated (as needed) to provide the level of detail needed based on the system being monitored. Connecting to the thin film detection layers is very easy as well. The truly unique feature of the system is its flexibility; the system can be designed to gather as much (or as little) information as the end user feels necessary. Individual detection layers can be turned on or off as necessary, and algorithms can be used to optimize performance. The system can be used to generate both diagnostic and prognostic information related to the health of layer composite structures, which will be essential if such systems are utilized for space exploration. The technology is also applicable to other in-situ health monitoring systems for structure integrity.

Williams, Martha↗

NASA NTRS2002

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s↗

NASA NTRS1995

Tensoral Present and Future

The coding of high-performance fluids simulations requires significant knowledge of both numerical and computational details. The magnitude and complexity of low-level details is often enough to discourage many users of turbulence data wishing to study more important, higher-level fluid dynamical questions. These same complexities are often a practical barrier to simulation experts who develop, verify and maintain the codes which generate this data. Future fluids codes, with high resolution and complex geometries, are likely to involve far more coding complexity. The research--the design and implementation of the Tensoral computer language--aims to greatly ease the coding of today's simulation and post-processing codes and at the same time provide a general computational tool for future simulations.

Dresselhaus, Eliot↗

NASA NTRS1990

Auto-programmable impulse neural circuits

Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

Watula, D.↗

NASA NTRS2007

Astronaut Risk Levels During Crew Module (CM) Land Landing

The NASA Engineering Safety Center (NESC) is investigating the merits of water and land landings for the crew exploration vehicle (CEV). The merits of these two options are being studied in terms of cost and risk to the astronauts, vehicle, support personnel, and general public. The objective of the present work is to determine the astronaut dynamic response index (DRI), which measures injury risks. Risks are determined for a range of vertical and horizontal landing velocities. A structural model of the crew module (CM) is developed and computational simulations are performed using a transient dynamic simulation analysis code (LS-DYNA) to determine acceleration profiles. Landing acceleration profiles are input in a human factors model that determines astronaut risk levels. Details of the modeling approach, the resulting accelerations, and astronaut risk levels are provided.

Lawrence, Charles↗

NASA NTRS1993

An architecture for object-oriented intelligent control of power systems in space

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

Holmquist, Sven G.↗

NASA NTRS2002

Deep Throttle Turbopump Technology Design Concepts

The objective of this project is to increase the throttling range of turbopumps from 30 to 120% of the design value, while maintaining high performance levels. Details are given on wide flow range issues, H-Q characteristics, stall characteristics, energy levels, pressure fluctuations at impeller exit, WFR impeller characteristics, commercial diffuser pumps, slotted or tandem vanes, leading edge characteristics, leading edge models, throat models, diffusion passage models, computational fluid dynamics (CFD) methodologies, and CFD flow cases.

Guinzburg, Adiel↗

NASA NTRS2005

A Program Certification Assistant Based on Fully Automated Theorem Provers

We describe a certification assistant to support formal safety proofs for programs. It is based on a graphical user interface that hides the low-level details of first-order automated theorem provers while supporting limited interactivity: it allows users to customize and control the proof process on a high level, manages the auxiliary artifacts produced during this process, and provides traceability between the proof obligations and the relevant parts of the program. The certification assistant is part of a larger program synthesis system and is intended to support the deployment of automatically generated code in safety-critical applications.

Denney, Ewen↗

NASA NTRS1981

Digital avionics design and reliability analyzer

The description and specifications for a digital avionics design and reliability analyzer are given. Its basic function is to provide for the simulation and emulation of the various fault-tolerant digital avionic computer designs that are developed. It has been established that hardware emulation at the gate-level will be utilized. The primary benefit of emulation to reliability analysis is the fact that it provides the capability to model a system at a very detailed level. Emulation allows the direct insertion of faults into the system, rather than waiting for actual hardware failures to occur. This allows for controlled and accelerated testing of system reaction to hardware failures. There is a trade study which leads to the decision to specify a two-machine system, including an emulation computer connected to a general-purpose computer. There is also an evaluation of potential computers to serve as the emulation computer.

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